diff options
Diffstat (limited to 'src/runtime/CPP')
| -rw-r--r-- | src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp | 8 | ||||
| -rw-r--r-- | src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp | 6 |
2 files changed, 7 insertions, 7 deletions
diff --git a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp index 13a34b43cd..e0acf06d49 100644 --- a/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionOutputLayer.cpp @@ -464,7 +464,7 @@ void CPPDetectionOutputLayer::run() // Ignore background class. continue; } - ARM_COMPUTE_ERROR_ON_MSG(_all_location_predictions[i].find(label) == _all_location_predictions[i].end(), "Could not find location predictions for label %d.", label); + ARM_COMPUTE_ERROR_ON_MSG_VAR(_all_location_predictions[i].find(label) == _all_location_predictions[i].end(), "Could not find location predictions for label %d.", label); const std::vector<BBox> &label_loc_preds = _all_location_predictions[i].find(label)->second; @@ -497,7 +497,7 @@ void CPPDetectionOutputLayer::run() const int label = _info.share_location() ? -1 : c; if(conf_scores.find(c) == conf_scores.end() || decode_bboxes.find(label) == decode_bboxes.end()) { - ARM_COMPUTE_ERROR("Could not find predictions for label %d.", label); + ARM_COMPUTE_ERROR_VAR("Could not find predictions for label %d.", label); } const std::vector<float> &scores = conf_scores.find(c)->second; const std::vector<BBox> &bboxes = decode_bboxes.find(label)->second; @@ -518,7 +518,7 @@ void CPPDetectionOutputLayer::run() if(conf_scores.find(label) == conf_scores.end()) { - ARM_COMPUTE_ERROR("Could not find predictions for label %d.", label); + ARM_COMPUTE_ERROR_VAR("Could not find predictions for label %d.", label); } const std::vector<float> &scores = conf_scores.find(label)->second; @@ -570,7 +570,7 @@ void CPPDetectionOutputLayer::run() { // Either if there are no confidence predictions // or there are no location predictions for current label. - ARM_COMPUTE_ERROR("Could not find predictions for the label %d.", label); + ARM_COMPUTE_ERROR_VAR("Could not find predictions for the label %d.", label); } const std::vector<BBox> &bboxes = decode_bboxes.find(loc_label)->second; const std::vector<int> &indices = it.second; diff --git a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp index 7b4f7b97c4..0addb0ead3 100644 --- a/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp +++ b/src/runtime/CPP/functions/CPPDetectionPostProcessLayer.cpp @@ -46,16 +46,16 @@ Status validate_arguments(const ITensorInfo *input_box_encoding, const ITensorIn ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->num_dimensions() > 3, "The location input tensor shape should be [4, N, kBatchSize]."); if(input_box_encoding->num_dimensions() > 2) { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->dimension(2) != kBatchSize, "The third dimension of the input box_encoding tensor should be equal to %d.", kBatchSize); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_box_encoding->dimension(2) != kBatchSize, "The third dimension of the input box_encoding tensor should be equal to %d.", kBatchSize); } - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_box_encoding->dimension(0) != kNumCoordBox, "The first dimension of the input box_encoding tensor should be equal to %d.", kNumCoordBox); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_box_encoding->dimension(0) != kNumCoordBox, "The first dimension of the input box_encoding tensor should be equal to %d.", kNumCoordBox); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_class_score->dimension(0) != (info.num_classes() + 1), "The first dimension of the input class_prediction should be equal to the number of classes plus one."); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_anchors->num_dimensions() > 3, "The anchors input tensor shape should be [4, N, kBatchSize]."); if(input_anchors->num_dimensions() > 2) { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input_anchors->dimension(0) != kNumCoordBox, "The first dimension of the input anchors tensor should be equal to %d.", kNumCoordBox); + ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR(input_anchors->dimension(0) != kNumCoordBox, "The first dimension of the input anchors tensor should be equal to %d.", kNumCoordBox); } ARM_COMPUTE_RETURN_ERROR_ON_MSG((input_box_encoding->dimension(1) != input_class_score->dimension(1)) || (input_box_encoding->dimension(1) != input_anchors->dimension(1)), |